Modules
Contents:
- Data
- Dataset
DatasetDataset.cache()Dataset.feature_schemaDataset.interactionsDataset.is_categorical_encodedDataset.item_countDataset.item_featuresDataset.item_idsDataset.load()Dataset.persist()Dataset.query_countDataset.query_featuresDataset.query_idsDataset.save()Dataset.subset()Dataset.to_pandas()Dataset.to_polars()Dataset.to_spark()Dataset.unpersist()
- DatasetLabelEncoder
DatasetLabelEncoderDatasetLabelEncoder.fit()DatasetLabelEncoder.fit_transform()DatasetLabelEncoder.get_encoder()DatasetLabelEncoder.interactions_encoderDatasetLabelEncoder.item_features_encoderDatasetLabelEncoder.item_id_encoderDatasetLabelEncoder.query_and_item_id_encoderDatasetLabelEncoder.query_features_encoderDatasetLabelEncoder.query_id_encoderDatasetLabelEncoder.transform()
- FeatureType
- FeatureSource
- FeatureHint
- FeatureInfo
- FeatureSchema
FeatureSchemaFeatureSchema.all_featuresFeatureSchema.categorical_featuresFeatureSchema.columnsFeatureSchema.copy()FeatureSchema.drop()FeatureSchema.filter()FeatureSchema.get()FeatureSchema.interaction_featuresFeatureSchema.interactions_rating_columnFeatureSchema.interactions_rating_featuresFeatureSchema.interactions_timestamp_columnFeatureSchema.interactions_timestamp_featuresFeatureSchema.item()FeatureSchema.item_featuresFeatureSchema.item_id_columnFeatureSchema.item_id_featureFeatureSchema.items()FeatureSchema.keys()FeatureSchema.numerical_featuresFeatureSchema.query_featuresFeatureSchema.query_id_columnFeatureSchema.query_id_featureFeatureSchema.subset()FeatureSchema.values()
- GetSchema
- Neural Networks
- Dataset
- Preprocessing
- Splitters
- Models
- RePlay Recommenders
- Recommender interface
- Distributed models
- Popular Recommender
- Query Popular Recommender
- Wilson Recommender
- Random Recommender
- UCB Recommender
- KL-UCB Recommender
- Thompson Sampling
- K Nearest Neighbours
- Alternating Least Squares
- Alternating Least Squares on Scala (Experimental)
- SLIM
- Word2Vec Recommender
- Association Rules Item-to-Item Recommender
- Cluster Recommender
- Neural models with distributed inference
- Wrappers and other models with distributed inference
- Neural Networks recommenders
- Metrics
- Scenarios
- Utils